The applicants plan to apply computational methods to assist in the search for optimal binding from sequence libraries. They specifically apply the algorithm to HIV TAR- Tat and other related RNA-peptide complexes. The method is iterative, and interactively calculates and refines RNA base-amino acid contact potentials to direct subsequent chemical combinatorial synthesis steps. In the first part of the project, the applicants will improve an existing algorithm that is capable of identifying most favorable base modifications that lead to better binding of a target peptide. They will then extend the computational methods to the reverse identification of the amino acid modifications that enhance peptide binding. The proposed iterative, integrated computational/experimental approach is self correcting and provides a rational basis for the development of software to expedite efficient sequence library searching. PROPOSED COMMERCIAL APPLICATION: Proposed commercial application not available.